FASSEG: a FAce Semantic SEGmentation repository for face image analysis (v2019)
Description
The FASSEG (v2019) repository is composed by four subsets containing face images useful for training and testing automatic methods for the task of face segmentation. Three subsets, namely frontal01, frontal02, and frontal 03 are specifically built for performing frontal face segmentation. Frontal01 contains 70 original RGB images and the corresponding roughly labelled ground-truth masks. Frontal02 contains the same image data, with high-precision labelled ground-truth masks. Frontal03 consists in 150 annotated face masks of twins captured in various orientations, illumination conditions and facial expressions. The last subset, namely multipose01, contains more than 200 faces in multiple poses and the corresponding ground- truth masks. For all face images, ground-truth masks are labelled on six classes (mouth, nose, eyes, hair, skin, and background).